Tetracycline Inducible Gene Manipulation in Serotonergic Neurons

The serotonergic (5-HT) neuronal system has important and diverse physiological functions throughout development and adulthood. Its dysregulation during development or later in adulthood has been implicated in many neuropsychiatric disorders. Transgenic animal models designed to study the contribution of serotonergic susceptibility genes to a pathological phenotype should ideally allow to study candidate gene overexpression or gene knockout selectively in serotonergic neurons at any desired time during life. For this purpose, conditional expression systems such as the tet-system are preferable. Here, we generated a transactivator (tTA) mouse line (TPH2-tTA) that allows temporal and spatial control of tetracycline (Ptet) controlled transgene expression as well as gene deletion in 5-HT neurons. The tTA cDNA was inserted into a 196 kb PAC containing a genomic mouse Tph2 fragment (177 kb) by homologous recombination in E. coli. For functional analysis of Ptet-controlled transgene expression, TPH2-tTA mice were crossed to a Ptet-regulated lacZ reporter line (Ptet-nLacZ). In adult double-transgenic TPH2-tTA/Ptet-nLacZ mice, TPH2-tTA founder line L62-20 showed strong serotonergic β-galactosidase expression which could be completely suppressed with doxycycline (Dox). Furthermore, Ptet-regulated gene expression could be reversibly activated or inactivated when Dox was either withdrawn or added to the system. For functional analysis of Ptet-controlled, Cre-mediated gene deletion, TPH2-tTA mice (L62-20) were crossed to double transgenic Ptet-Cre/R26R reporter mice to generate TPH2-tTA/Ptet-Cre/R26R mice. Without Dox, 5-HT specific recombination started at E12.5. With permanent Dox administration, Ptet-controlled Cre-mediated recombination was absent. Dox withdrawal either postnatally or during adulthood induced efficient recombination in serotonergic neurons of all raphe nuclei, respectively. In the enteric nervous system, recombination could not be detected. We generated a transgenic mouse tTA line (TPH2-tTA) which allows both inducible and reversible transgene expression and inducible Cre-mediated gene deletion selectively in 5-HT neurons throughout life. This will allow precise delineation of serotonergic gene functions during development and adulthood

Network Meta-Analysis of Multiple Outcomes: A Simulation Study and Application

The usefulness of a multivariate approach to compare treatments in the context of pairwise meta-analysis has been widely demonstrated in the literature. However, this approach has not yet been considered for multiple treatment comparisons. We believe that extending such methodology to network meta-analysis (NMA) will increase the primary evidence base allowing us to compare more interventions across multiple outcomes measures. Borrowing strength between outcome measures using multivariate NMA can also potentially increase the precision of relative treatment effect estimates and reduce the impact of outcome reporting bias. Objectives To extend standard NMA to incorporate multiple outcomes of interest and evaluate the use of multivariate NMA models through simulated and real datasets. Methods We developed a random effects multivariate NMA model to account for the correlation between multiple outcome measures. The potential benefits of this method were demonstrated in a simulated example comparing univariate and bivariate NMAs for continuous outcome measures. We further explored the application of our multivariate NMA model using a case study comparing anti-obesity pharmacological interventions for waist circumference, weight change and BMI change from baseline. Results The simulation study showed that through use of multivariate NMA the precision in mean relative treatment effects increased compared to a standard univariate NMA. This held true under multiple scenarios testing model parameters including both within- and between-outcome correlations. Similar findings were obtained from the application to the example dataset in obesity. Conclusions Our method proves particularly useful in reducing uncertainty around relative effectiveness estimates when the outcomes included for analysis are highly correlated. However, the advantages of the multivariate NMA are limited where there is little correlation between outcome measures. Further work will explore the applicability of multivariate NMA methods to different types of outcomes such as binary outcome measures

Network Meta-Analysis of Multiple Outcomes: A Simulation Study and Application

The usefulness of a multivariate approach to compare treatments in the context of pairwise meta-analysis has been widely demonstrated in the literature. However, this approach has not yet been considered for multiple treatment comparisons. We believe that extending such methodology to network meta-analysis (NMA) will increase the primary evidence base allowing us to compare more interventions across multiple outcomes measures. Borrowing strength between outcome measures using multivariate NMA can also potentially increase the precision of relative treatment effect estimates and reduce the impact of outcome reporting bias. Objectives To extend standard NMA to incorporate multiple outcomes of interest and evaluate the use of multivariate NMA models through simulated and real datasets. Methods We developed a random effects multivariate NMA model to account for the correlation between multiple outcome measures. The potential benefits of this method were demonstrated in a simulated example comparing univariate and bivariate NMAs for continuous outcome measures. We further explored the application of our multivariate NMA model using a case study comparing anti-obesity pharmacological interventions for waist circumference, weight change and BMI change from baseline. Results The simulation study showed that through use of multivariate NMA the precision in mean relative treatment effects increased compared to a standard univariate NMA. This held true under multiple scenarios testing model parameters including both within- and between-outcome correlations. Similar findings were obtained from the application to the example dataset in obesity. Conclusions Our method proves particularly useful in reducing uncertainty around relative effectiveness estimates when the outcomes included for analysis are highly correlated. However, the advantages of the multivariate NMA are limited where there is little correlation between outcome measures. Further work will explore the applicability of multivariate NMA methods to different types of outcomes such as binary outcome measures

Autonomic nervous system involvement in the giant axonal neuropathy (GAN) KO mouse: implications for human disease

PURPOSE: Giant axonal neuropathy (GAN) is an inherited severe sensorimotor neuropathy. The aim of this research was to investigate the neuropathologic features and clinical autonomic nervous system (ANS) phenotype in two GAN knockout (KO) mouse models. Little is known about ANS involvement in GAN in humans, but autonomic signs and symptoms are commonly reported in early childhood. METHODS: Routine histology and immunohistochemistry was performed on GAN KO mouse specimens taken at various ages. Enteric dysfunction was assessed by quantifying the frequency, weight, and water content of defecation in GAN KO mice. RESULTS: Histological examination of the enteric, parasympathetic and sympathetic ANS of GAN KO mice revealed pronounced and widespread neuronal perikaryal intermediate filament inclusions. These neuronal inclusions served as an easily identifiable, early marker of GAN in young GAN KO mice. Functional studies identified an age-dependent alteration in fecal weight and defecation frequency in GAN KO mice. CONCLUSIONS: For the first time in the GAN KO mouse model, we described the early, pronounced and widespread neuropathologic features involving the ANS. In addition, we provided evidence for a clinical autonomic phenotype in GAN KO mice, reflected in abnormal gastrointestinal function. These findings in GAN KO mice suggest that consideration should be given to ANS involvement in human GAN, especially when considering treatments and patient care

C-elegans ring finger protein RNF-113 is involved in interstrand DNA crosslink repair and interacts with a RAD51C homolog

The Fanconi anemia (FA) pathway recognizes interstrand DNA crosslinks (ICLs) and contributes to their conversion into double-strand DNA breaks, which can be repaired by homologous recombination. Seven orthologs of the 15 proteins associated with Fanconi anemia are functionally conserved in the model organism C. elegans. Here we report that RNF-113, a ubiquitin ligase, is required for RAD-51 focus formation after inducing ICLs in C. elegans. However, the formation of foci of RPA-1 or FCD-2/FANCD2 in the FA pathway was not affected by depletion of RNF-113. Nevertheless, the RPA-1 foci formed did not disappear with time in the depleted worms, implying serious defects in ICL repair. As a result, RNF-113 depletion increased embryonic lethality after ICL treatment in wild-type worms, but it did not increase the ICL-induced lethality of rfs-1/rad51C mutants. In addition, the persistence of RPA-1 foci was suppressed in doubly-deficient rnf-113;rfs-1 worms, suggesting that there is an epistatic interaction between the two genes. These results lead us to suggest that RNF-113 and RFS-1 interact to promote the displacement of RPA-1 by RAD-51 on single-stranded DNA derived from ICLs